讲座题目 | Different Opinion or Information Asymmetry: Machine-Based Measure and Consequences | ||
主讲人 （单位） | 刘扬 （湖南大学） | 主持人 （单位） | 汪琼 （必威BETWAY官网） |
讲座时间 | 2025年6月13日（周五） 10：00 | 讲座地点 | 经管楼B203会议室 |
主讲人简介 |
刘扬，湖南大学金融与统计学院助理教授，获清华大学金融学博士学位，中央财经大学金融工程学士学位，圣路易斯华盛顿大学奥林商学院访问学者。研究领域为实证资产定价、金融科技。作为项目负责人主持国家自然科学基金、教育部人文社科基金等多个项目。其研究成果发表于The Review of Asset Pricing Studies等高水平期刊，多篇工作论文入选AFA和CICF等知名学术会议。 | ||
讲座内容摘要 | We leverage machine learning to introduce belief dispersion measures to distinguish different opinion (DO) and information asymmetry (IA). Our measures align with the human-based measure and relate to economic outcomes in a manner consistent with theoretical prediction: DO negatively relates to illiquidity, while IA positively does. Moreover, IA negatively predicts the cross-section of stock returns, while DO predicts returns positively for underpriced stocks and negatively for overpriced ones. Our findings reconcile conflicting disagree-return relations in the literature and are consistent with Atmaz and Basak (2018)'s model. We also show that the return predictability of DO and IA stems from their unique economic rationales, underscoring that components of disagreement can influence market equilibrium via distinct mechanisms. | ||
